Whether you run open source, Cloudera, or another distribution, Bigstream speeds your Spark jobs by up to 10x
Hyperacceleration improves performance of data platforms like Apache Spark by automatically optimizing them with compute hardware.
The flexible approach gives access to cloud hardware like AWS’s F1 FPGA instances with no impact on user Spark code.
Rein in Your AWS Bills
In the cloud, Total Cost of Ownership (TCO) is simple. Time really is money when cutting job completion time directly cuts your cloud usage costs.
Amazon provides a variety of instance types to balance the mix of compute, memory, and storage. Adding FPGAs to the equation provides a much bigger performance boost.
Add AWS F1 instances with FPGAs to your Spark on EC2 deployment and see results immediately.
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Sign up for a free 30-day trial and we’ll show you the details of your acceleration and your savings.
The value of Bigstream is that it automatically provides the communication and translation between Spark code and the computing environment.
While other acceleration approaches force you to alter your code or switch platforms entirely, with Bigstream your Spark code remains 100% unchanged.
Jobs run up to 10X faster without changing your Apache Spark code, increasing data science productivity and the ability to meet tight SLAs
Incorporate fuller data sets and more data sources by eliminating the bottlenecks forcing you to make compromises
Instead of scale-out and scale-up, optimize your existing Spark environment with Bigstream, lowering hardware and operating expenses
